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Analysis of Kazakhstan Oil Shale Deposits in Accordance with Resource Estimation Practices for Consideration of Potential Shale Oil Reserves
by
Sabanov, Sergei
, Korshunova, Ruslana
, Konist, Alar
in
Analysis
/ Carbon
/ Coal
/ fault tree
/ Geology
/ Hydrogen
/ Mineral reserves
/ Mineral resources
/ Monte Carlo method
/ Nitrogen
/ Oil reserves
/ Oil shale
/ Oil-shales
/ Petroleum
/ Petroleum mining
/ probability distribution
/ Rankings
/ Reserves
/ retorting
/ Shale oil
/ shale oil reserves
/ Shale oils
/ Sulfur content
2025
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Analysis of Kazakhstan Oil Shale Deposits in Accordance with Resource Estimation Practices for Consideration of Potential Shale Oil Reserves
by
Sabanov, Sergei
, Korshunova, Ruslana
, Konist, Alar
in
Analysis
/ Carbon
/ Coal
/ fault tree
/ Geology
/ Hydrogen
/ Mineral reserves
/ Mineral resources
/ Monte Carlo method
/ Nitrogen
/ Oil reserves
/ Oil shale
/ Oil-shales
/ Petroleum
/ Petroleum mining
/ probability distribution
/ Rankings
/ Reserves
/ retorting
/ Shale oil
/ shale oil reserves
/ Shale oils
/ Sulfur content
2025
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Do you wish to request the book?
Analysis of Kazakhstan Oil Shale Deposits in Accordance with Resource Estimation Practices for Consideration of Potential Shale Oil Reserves
by
Sabanov, Sergei
, Korshunova, Ruslana
, Konist, Alar
in
Analysis
/ Carbon
/ Coal
/ fault tree
/ Geology
/ Hydrogen
/ Mineral reserves
/ Mineral resources
/ Monte Carlo method
/ Nitrogen
/ Oil reserves
/ Oil shale
/ Oil-shales
/ Petroleum
/ Petroleum mining
/ probability distribution
/ Rankings
/ Reserves
/ retorting
/ Shale oil
/ shale oil reserves
/ Shale oils
/ Sulfur content
2025
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Analysis of Kazakhstan Oil Shale Deposits in Accordance with Resource Estimation Practices for Consideration of Potential Shale Oil Reserves
Journal Article
Analysis of Kazakhstan Oil Shale Deposits in Accordance with Resource Estimation Practices for Consideration of Potential Shale Oil Reserves
2025
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Overview
Most oil shale deposits in Kazakhstan were estimated without detailed calculations of the grade and tonnages and included low confidence categories, i.e., Inferred, Off-Balance, and Non-Economic oil shales, on which cannot be given any oil reserves. An analysis of Kazakhstan oil shale deposits in accordance with resource estimation practices for consideration of potential shale oil tonnages has been produced. The developed methodology considers extraction and processing recoveries of conventional and unconventional mining methods. The methodology uses Monte Carlo modeling to estimate a range of oil content and oil recoveries and uses the event tree analysis to demonstrate how the initial oil shale material tonnages and grades go through various fault and success branches, considering probabilities distributions and estimating potential shale oil tones at the end. As a result, this estimation methodology has been validated by high-ranked resource category oil shale deposits, which demonstrated the range of potential shale oil in the range of 10.7–16.8 Mt at the 50% confidence level. The results will be used for further consideration in financial-economic feasibility studies, which must take into account operational and capital expenses, product sale prices and market, and social-environmental aspects.
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